Can you imagine a world where UPSTM or FEDEXTM, the trucking sector, the busing sector, or many other highly efficient, cost-effective sectors didn’t use algorithms and software to get food to your grocery store or the latest gadget to your door? You might be surprised to know that our health system delivers millions of home care visits every year, without the benefit of those same tools.

HCI considers these issues in our position paper on health system innovation in Ontario. In the same way that businesses adapt to their changing markets—reducing costs, adding value for customers, and improving productivity—so too must health systems adapt.

While the paper focuses on system level impacts for the Province of Ontario, the concepts within are fully applicable to the stakeholders in any single-payor jurisdiction. Logistics tools that have long been available in most other sectors are finally ready for the challenging future of home care and patient-focused outcomes.

Homecare Intelligence, Inc. provides several options to assist homecare logistics and scheduling operations. Each of these optimization option solutions comes with it’s own benefits and it’s own conditions and data requirements. In speaking with various companies across the post-acute care spectrum, we’ve found that it’s often easier to talk about these solutions in terms of level of sophistication. The levels of service described below are given in order of increasing data demands, complexity and strategic value, from tactical assistance to broader horizon strategic planning.

Level 0: Geocoding of resources and consumers

Geocoding converts resource and consumer addresses into latitude and longitude for mapping purposes. This is useful for basic patient and clinician map production and analysis and is the starting point for all geo-spatial analysis activities.

Level 1: Ordered service routing

Basic non-optimized routing services. Takes an existing visit schedule (in a given order) and returns the driving statistics (individual route legs and total driving distance and time) for a single staff on a given day.

Benefits Builds an accurate picture of miles driven and time spent driving from visit-to-visit for particular clinician on a particular day.

Level 2: Service route optimization

Optimized routing takes a list of waypoints, and returns the optimal order and driving statistics (individual route legs and total driving distance and time) for a single staff on a given day. In addition, it provides the “optimal” order for the visits. It is mainly used by a clinician at the beginning of the day to help them determine the best order to perform the day’s visits. Can be configured to account for specific requirements around clinician and patient availability or delivery times.

Typical Use Case Modifying the order of the day’s scheduled visits to be put in the optimal sequence from a driving distance and time perspective.

Benefits Reorders a visit plan to ensure driving distance and time are kept to a minimum.

Optional Ability to add time windows if certain visits need to be performed at a specific time or within a range of times (time window).

Level 3: Single event optimization

Given the dynamic nature of homecare, there is often a need to fit a visit into an established service schedule. The goal of this form of optimization is to produce a list of clinicians that are the best suited to a newly added (or changed) service based on the assigned visits for the day and the existing fleet driving routes.

Typical Use Case Generally used to provide ad-hoc clinician recommendations for visits. For example, if a clinician calls in sick (or a patient needs a visit on the current day, etc), this process will examine all the clinicians and create a recommended list of clinicians to perform the visit. The recommendation takes into account the clinician’s current schedule, where they will be driving during the day, and the marginal impact of adding the visit to the current schedule. It will also take into account any patient preferences (both soft and hard constraints) into the calculation.

Request Requirements Visit type, visit date, any custom attributes. Optional: list of clinicians, along with existing visit locations, to be considered for recommendation.

Data Requirements Existing fleet schedule consisting of visit types, clinicians with locations and visit types they can perform, current clinician fleet schedule for day and their individual availabilities.

Benefits Accommodates the dynamic nature of providing homecare services by helping agencies cope with the constant schedule modifications necessary to fit daily changes to service demands.

Optional Ability to add time windows if certain visits need to be performed at a specific time or within a range of times (time window). Also can be configured to prefer para-professional staff (i.e. RN vs LPN, PT vs PTA, etc.)

As a real-world example, in the Homecare Intelligence product, the visit optimization process will honor any territories that have been established for the clinician. The “Dist” column is the closest approximate “as-the-crow” flies distance between the patient and either: 1) the clinician’s home or 2) one of the other visits the clinician is performing on the day.

To get the true driving time, the user can click the “Score” button. This will calculate the optimized routing distance and time for the existing schedule, then calculate the optimized routing distance and time if the visit is added to the clinician’s schedule for the day.

In the above case, after the scoring is complete, the distance now shows “6.0”. This means that if you add this visit to the clinician’s schedule, it will result in an extra 6 miles of driving to the day’s driving.

You can now get the optimized driving route for the day, with the new visit, by clicking the clinician’s name:

Level 4: Daily optimization

Daily optimization is a holistic approach to daily patient visit planning. For a given clinician/patient grouping, (provider branch, fleet, etc.) daily optimization takes into account all the visits that need service for a given day, plus all the clinicians that are available and determines the best schedules “as a whole”. The process minimizes total drive time and distance over an entire organization location while keeping in mind service constraints (i.e. skilled nurse visit with wound care), preferences (i.e. patient prefers Spanish speakers). The algorithm will maximize the productivity of the clinician resources, based on the visit demand.

Benefits Minimizes overall drive time and increases staff productivity by recommending the right staff to assign to a given service, while holding all provided constraints in balance. Particularly useful in situations where patient continuity of care is not a top priority (staffing services, etc.).

Optional Ability to add time windows if certain visits need to be performed at a specific time or within a range of times (time window). Also can be configured to prefer para-professional staff (i.e. RN vs LPN, PT vs PTA, etc.)

Level 5: Consumer assignment optimization

Consumer assignment optimization is a long-range visit planning process. The goal is to identify the best “primary” clinician who can perform the greatest number of visits, thereby increasing patient continuity of care. The process will examine the patient visit requirements for the entire episode and examine all the clinicians’ schedules, location and current patient load to create the recommendation list. The result is a prioritized list of clinicians that are best suited to be the primary or main clinician for a given patient over the course of an episode of care. In the event a single clinician cannot perform 100% of the estimated patient visits, the algorithm will also return an alternate clinician recommendation list for the remaining, unassigned, visits.

Typical Use Case At time of admission, the scheduler will run the primary optimization process to get a list of recommended clinicians to act as primary or case manager.

Request Requirements Patient location, list of patient visits.

Data Requirements Visit types, clinicians with locations and visit types they can perform, clinician current schedule for entire period and availability.

Benefits Enables long-range planning in the assignment of a primary (and alternate) clinicians to particular patient services. Increases patient continuity of care. Helps “cluster” clinician patients in as small an area as possible.

Optional Ability to add time windows if certain visits need to be performed at a specific time or within a range of times (time window).

Patient optimization can take into account many factors, but it should first and foremost be focused on clinician continuity.